Grafana
Grafana is an open-source platform for data visualisation, monitoring and observability. It is used to collect, visualise and analyse real-time data from a wide range of data sources via dashboards, charts, alarms and trend analysis.
Within Industrial Automation and OT environments, Grafana is increasingly applied for monitoring production processes, energy consumption, network status, machine performance and Cybersecurity events. Thanks to its broad support for data sources and protocols, Grafana often serves as a central visualisation layer within modern IT OT Convergence architectures.
Grafana is widely used in combination with:
Thanks to its flexibility and Scalability, Grafana can be deployed from small edge installations through to large-scale industrial monitoring platforms.
⚙️ How Grafana works
By default, Grafana does not store process data itself, but functions as a visualisation and analysis platform on top of data sources.
The Architecture typically consists of:
- Data sources collect data
- Grafana retrieves data via connectors
- Dashboards visualise the data
- Alarms generate notifications
- Users analyse trends and events
Grafana supports both real-time and historical data analysis.
Frequently used data sources:
| Data source | Application |
|---|---|
| Prometheus | Metrics monitoring |
| InfluxDB | Time series data |
| Elasticsearch | Logging |
| PostgreSQL | Relational data |
| Loki | Log management |
| OPC UA gateways | OT data |
| MQTT brokers | IIoT data |
Grafana can be deployed both On-Premise and in cloud environments.
🏭 Applications in industrial automation
Within Industrial Automation, Grafana is used for:
Process monitoring
- Temperature trends
- Pressure measurements
- Flow rates
- Energy consumption
- Production output
Machine monitoring
- Vibration monitoring
- Motor loading
- Failure frequencies
- Cycle times
- OEE analyses
OT Network Monitoring
Cybersecurity
- Security dashboards
- Event correlation
- SIEM integration
- Threat Hunting
- Incident detection
Grafana is often used as a complementary visualisation layer alongside traditional SCADA systems.
🧠 Architecture in OT environments
Grafana usually resides in a higher OT or IT layer of the Automation Pyramid.
A typical architecture:
| Layer | Component |
|---|---|
| Field layer | Sensor, PLC |
| Control layer | SCADA, DCS |
| Historian layer | Historian, InfluxDB |
| Visualisation layer | Grafana |
| Enterprise layer | MES, ERP |
Data is often delivered via:
In this setup, Grafana acts as a central observability interface.
📊 Dashboards and visualisations
Grafana supports extensive dashboard functionality.
Typical visualisations:
- Line charts
- Heatmaps
- Gauges
- Tables
- Alarm overviews
- Sankey diagrams
- State timelines
Within OT, dashboards are used for:
- Process trending
- Alarm analysis
- Energy management
- Predictive Maintenance
- Security Monitoring
Dashboards can include real-time updates at intervals from milliseconds to minutes.
🔄 Time series data
Grafana is strongly focused on processing time series data.
Characteristics of industrial time series data:
- High measurement frequency
- Large datasets
- Continuous data streams
- Historical trend analysis
- Event correlation
For this reason, Grafana often works together with:
- Historian
- Time Series Database
- InfluxDB
- Prometheus
Typical OT data:
| Parameter | Example |
|---|---|
| Temperature | Furnace process |
| Pressure | Hydraulic system |
| Vibration | Predictive maintenance |
| Energy | Power analysis |
| Status bits | Machine conditions |
🌐 Integration with industrial protocols
Grafana usually communicates indirectly with OT Assets via middleware or gateways.
Frequently used OT integrations:
| Protocol | Application |
|---|---|
| OPC UA | Industrial data exchange |
| MQTT | IIoT streaming |
| Modbus TCP | PLC data |
| ProfiNET | Machine integration |
| Ethernet IP | Industrial networks |
A broker, historian or edge platform is often used as an intermediate layer.
Examples:
📈 Monitoring and observability
Grafana often forms part of broader observability platforms.
Key observability components:
| Component | Function |
|---|---|
| Metrics | Performance data |
| Logs | Event analysis |
| Traces | Process flows |
| Alerts | Incident detection |
Within OT, Grafana supports:
- Condition Monitoring
- Predictive Maintenance
- Energy management
- Network monitoring
- Asset monitoring
Grafana is frequently combined with:
- Prometheus
- Loki
- Tempo
- Elasticsearch
🚨 Alarms and notifications
Grafana supports advanced alerting.
Alarms can be based on:
- Threshold values
- Trends
- Deviations
- Complex queries
Notifications can be sent via:
- Microsoft Teams
- Slack
- Webhooks
- SMS platforms
For OT environments, correct alarm prioritisation is important to prevent alarm flooding.
Grafana is therefore regularly integrated with Alarm Management processes.
🔐 Cybersecurity and security monitoring
Grafana is increasingly used within OT security monitoring.
Applications:
- SIEM dashboards
- Threat visibility
- Network monitoring
- Vulnerability overviews
- Incident Response dashboards
Possible data sources:
Key risks:
| Risk | Consequence |
|---|---|
| Weak authentication | Unauthorised access |
| Poor segmentation | Lateral movement |
| Public dashboards | Data leaks |
| Outdated plugins | Exploits |
Key controls:
Within industrial environments, Grafana must be carefully positioned within the OT Architecture.
⚠️ Availability and performance
Grafana is frequently used for business-critical monitoring.
Key design choices:
- Redundant databases
- Load balancing
- Retention policy
- Query optimisation
- Edge buffering
Performance problems often arise from:
- Large queries
- High cardinality
- Overloaded data sources
- Poor dashboard design
In large OT environments, scalability can be crucial.
🧩 Plugins and extensions
Grafana supports a large plugin ecosystem.
Categories:
| Type | Examples |
|---|---|
| Data sources | OPC UA, MQTT |
| Panels | Heatmaps, gauges |
| Integrations | Cloud platforms |
| Security plugins | SSO, LDAP |
In industrial environments, plugin management is important because of security and lifecycle risks.
Uncontrolled plugins can:
- Introduce vulnerabilities
- Cause performance issues
- Create compatibility problems
☁️ Cloud, edge and hybrid OT architectures
Grafana supports multiple deployment models.
On-premise
Widely used in:
- Critical Infrastructure
- Production environments
- Segmented OT networks
Cloud
Advantages:
- Scalability
- Centralised analytics
- Multi-site monitoring
Edge deployment
Applied for:
- Low Latency
- Time-critical processes
- Limited connectivity
Grafana is frequently deployed within Edge Computing architectures.
🔄 Grafana versus traditional SCADA
| Property | Grafana | SCADA |
|---|---|---|
| Primary purpose | Visualisation and analytics | Process control |
| Real-time control | Limited | Full |
| Historical analysis | Strong | Depends on the system |
| Open integrations | Very broad | Vendor-dependent |
| Alarm management | Good | Very extensive |
| Industrial certification | Limited | Often present |
| OT-native | No | Yes |
Grafana usually does not replace a SCADA system, but acts as a complementary observability and analysis environment.
🏗️ Grafana in IT/OT convergence
Within IT OT Convergence, Grafana plays an important role as a unified visualisation layer between the IT and OT domains.
Benefits:
- Centralised dashboards
- Cross-domain Monitoring
- Security visibility
- Energy analysis
- Predictive Maintenance
Grafana thereby supports:
- Data-driven production
- Industry 4.0
- Unified observability
- Asset intelligence
- Cloud integration
At the same time, challenges arise around:
- Data quality
- Security
- Segmentation
- Lifecycle Management
- Governance
Grafana thus represents an important platform within modern industrial observability architectures.